OBO Foundry dashboard analysis¶

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/tmp/ipykernel_535/4293058459.py:21: FutureWarning:

The `inplace` parameter in pandas.Categorical.reorder_categories is deprecated and will be removed in a future version. Reordering categories will always return a new Categorical object.

Ontologies by number of axioms

Ontologies by number of classes

Ontologies by how many ontologies use it

Different serialisations used

RDF/XML Syntax    4
unknown           1
Name: syntax, dtype: int64

Breakdown of used Axiom Types

count mean std min 25% 50% 75% max
AnnotationAssertion 4 79031.4 165919.598057 0.0 2.0 8675.0 10773.0 375707.0
Declaration 4 7956.8 13726.474445 0.0 2.0 1989.0 5628.0 32165.0
EquivalentClasses 4 2239.0 3305.080937 0.0 1.0 584.0 2842.0 7768.0
SubAnnotationPropertyOf 2 7.8 16.887865 0.0 0.0 0.0 1.0 38.0
SubClassOf 2 9570.4 20753.845024 0.0 0.0 0.0 1167.0 46685.0
DisjointClasses 1 15.6 34.882660 0.0 0.0 0.0 0.0 78.0
SubObjectPropertyOf 1 0.8 1.788854 0.0 0.0 0.0 0.0 4.0
SubPropertyChainOf 1 1.4 3.130495 0.0 0.0 0.0 0.0 7.0
SymmetricObjectProperty 1 0.2 0.447214 0.0 0.0 0.0 0.0 1.0

Breakdown of used OWL Class Expression constructs

count mean std min 25% 50% 75% max
Class 4 34023.4 64761.813647 0.0 3.0 6184.0 14550.0 149380.0
ObjectSomeValuesFrom 4 4614.4 7965.189627 0.0 1.0 1151.0 3257.0 18663.0
ObjectIntersectionOf 3 2279.4 3287.162880 0.0 0.0 717.0 2926.0 7754.0
ObjectUnionOf 1 2.8 6.260990 0.0 0.0 0.0 0.0 14.0

OBO Score (Experimental)

ontology score score_dash score_impact
2 maxo 0.564 0.727 0.4
0 ecto 0.522 0.844 0.2
3 mondo 0.474 0.949 0.0
4 tmp 0.141 0.282 0.0
1 hpo 0.000 0.000 0.0

OBO Score Summary

count mean std min 25% 50% 75% max
score 5.0 0.3402 0.253208 0.0 0.141 0.474 0.522 0.564
score_dash 5.0 0.5604 0.403345 0.0 0.282 0.727 0.844 0.949
score_impact 5.0 0.1200 0.178885 0.0 0.000 0.000 0.200 0.400

OBO dependency graph